Calculating worklife expectancy value for partial disability
People with a disability experience significantly higher rates of unemployment than people with no disability. Employment levels are the primary building blocks of a worklife expectancy.
Men and women across all levels of educational attainment with a disability experience significantly higher levels of unemployment than persons with no disability. This is supported by data emanating from numerous government sources and holds true regardless of how disability is defined. Whether it is a physical disability, a cognitive disability, a sensory disability, or a work disabling condition, persons with a disability experience lower levels of employment. The following surveys all show reduced employment levels for disabled individuals: Annual Social and Economic Supplement (ASEC, or the March Supplement) to the Current Population Survey (CPS), the Survey of Income and Program Participation (SIPP), and the American Community Survey (ACS) from the U.S. Census Bureau (2013); the National Health Interview Survey (NHIS) from the National Center for Health Statistics; the N.O.D./Harris Survey of Americans With Disabilities; and the Behavioral Risk Factor Surveillance System (BRFSS) conducted by the Centers for Disease Control and Prevention.
It is generally accepted that disability has a negative effect on employment. What is often overlooked is that employment levels are the primary building blocks of a worklife expectancy value.
The purpose of this article is to assist attorneys who represent clients with a partial disability in understanding the importance of having an expert use the government data that permits the calculation of a worklife expectancy value. Reduction of worklife expectancy for an individual who is currently employed or clearly capable of employment is essential in order to obtain an adequate award associated with earning capacity loss. The reduction of worklife expectancy must be considered, particularly when an individual has returned to work earning more money than earned prior to injury.
Worklife expectancy is a statistical average, derived by summing a series of joint probabilities of life, participation, and employment (LPE) from a given age through the life expectancy. The worklife methodology used in a vocational economic assessment was introduced as the LPE method by Brookshire and Cobb (1983) and refined by Brookshire, Cobb, and Gamboa (1987) to include persons with a work disability (Brookshire, Michael L., and William E. Cobb. 1983. “The Life-Participation-Employment Approach to Worklife Expectancy in Personal Injury and Wrongful Death Cases.” For the Defense, 20-25. & Brookshire, Michael L., William E. Cobb, and Anthony M. Jr. Gamboa. 1987. “Work-Life of the Partially Disabled.” Trial.) With this methodology, a person’s earning capacity is reduced by the probability of being alive and employed.
It is interesting to note that a federal appellate court decision, O’ Shea v. Riverway Towing (7th Cir. 1982) 677 F. 2d 1194, advocates a method of assessing “the expectation of earnings” that preceded the 1983 publication of Brookshire and Cobb. In that decision, it is noted that the economist performing the assessment of earning capacity loss neglected to consider probable levels of employment either before or after injury. The decision proposed what is generally considered probabilistic decision making which makes use of probability data specific to a circumstance. With regard to the plaintiff’s before injury earnings, the decision stated the following:
If the probability of her being employed as a boat’s cook full time in 1980 was only 75 percent, for example, then her estimated wages in that year should have been multiplied by .75 to determine the value of the expectation that she lost as a result of the accident and so with each of the other future years.
(Id., 677 F.2d at p. 1200.)
By way of example, O’Shea in the late 1970’s worked as a cook on a boat, a position she obtained shortly after the death of her husband. With earnings of $10,000 per year, the decision advocated a reduction of the $10,000 figure to $7,500 by multiplying the earnings figure by the assumed employment probability of .75.
If it is assumed that the 55-year-old plaintiff would have retired at 65 years of age, then the expected worklife would have been 7.5 years instead of 10 years because each year would have represented a .75 probability of employment. It is the summation of the separate probabilities of employment that produces a worklife expectancy in years.
The decision further states that a similar approach to probabilistic decision making should have been considered after injury. It is noted that “the plaintiff is overweight, in constant and significant pain, with no specific skills other than cooking, a job requiring long periods of standing for which she is incapable.” It then states the following:
It seems unlikely that someone in this condition could find gainful work at the minimum wage. True, the probability is not zero; and a better procedure, therefore, might have been to subtract from Mrs. O’Shea’s lost future wages as a boat’s cook the wages in some other job, discounted (i.e., multiplied) by the probability-very low-that she would in fact be able to get another job.
(Id., 677 F.2d at p. 1197.)
The opinion defines a method for estimating future expected earnings: that of utilizing probability statistics to better define future expected earnings in assisting the trier of fact. The O’Shea case involves a woman with a severe work disability. The probability of employment for a 55-year-old female high school graduate with a severe physical disability is roughly .12, compared to a probability of employment of .75 for a female of the same age and education with no disability (probabilities of employment for individuals with and without disability can be found by utilizing DataFerrett, a tool provided by the U.S. Census Bureau at: http://dataferrett.census.gov/AboutDatasets/ACS.html). Before her injury, O’Shea’s worklife expectancy would have been 7.5 years. Now that she suffers a severe physical disability, government data shows us that individuals most like her will have a worklife expectancy of 1.2 years or .12 multiplied by 10 years, again assuming retirement at age 65.
The American Community Survey (ACS) is a macro study commissioned by the Congress of the United States to augment the decennial census by providing more up to date demographic data. With an annual sample size of 3.6 million, it is an excellent source of employment data. It provides such data for men and women at various levels of educational attainment without and with various types of disability. It is the single best data source for computing worklife expectancy values for persons with a disability.
A tempest in a teapot
There are numerous possible causes for the reduced levels of employment experienced by workers with physical or mobility disabilities. These workers may experience reduced productivity due to physically moving slower, distracting pain, required medications, additional doctor visits, need for accommodation, reduced opportunities, or employer prejudice. An attorney with a mobility disability may need to leave for court or a meeting earlier to adjust for being unable to take stairs. A doctor may be unable to work in an emergency room because it requires standing and walking for prolonged periods of time. A machine operator may require additional breaks to manage pain. A warehouse worker may only be able to stock items under 30 pounds, leaving heavier items for coworkers. A worker may have the opportunity to spend extra time at work to increase their production, but doing so takes time from other facets of their life. New challenges created by a disability in an individual’s life can create stress or distraction at work and lead to difficulties.
A cognitive disability can have obvious consequences on a worker’s worklife expectancy. A brain injury can reduce work efficiency, require outside oversight, diminish concentration or memory, or dramatically increase stress and fatigue. A worker’s training and the application of their skills can be affected by a brain injury. An individual with a cognitive disability could have trouble with time management, difficulty learning new materials, or be prone to emotional outbursts. Each individual case of cognitive disability has unique characteristics, but all instances share the fact that the affected individual’s ability to work has been negatively impacted due to injury.
Measuring worklife expectancy for disabled individuals has been criticized by several forensic economists in forensic economics journals. A large majority of articles criticizing the use of government data in arriving at a reduced worklife expectancy for an individual with a disability have been published in either the Journal of Forensic Economics or the Journal of Legal Economics (Ciecka, James E., James D. Rodgers, and Gary R. Skoog. 2002. The New Gamboa Tables: A Critique. Journal of Legal Economics 12(2): pp. 101-107; Ireland, Thomas. 2009. “Why the Gamboa-Gibson Disability Work-Life Expectancy Tables Are Without Merit.” Journal of Legal Economics 15(2): pp. 105-109; Jones, David D. 2005. “Problems with Government Measures of Disability to Estimate Potential Earnings Loss.” Journal of Forensic Economics 18(2-3): pp. 155-170; Skoog, Gary R. and David C. Toppino. 1999. “Disability and the New Worklife Expectancy Tables from Vocational Econometrics, 1998: A Critical analysis.” Journal of Forensic Economics 12(3): pp. 239-54; Ostrofe, Nora C. 2014. “Does the Vocational Economic Rationale Have Merit? – An Appraisal.” Journal of Legal Economics 20 (1-2): pp. 61-83.). However, the reputability of the two main journals that have published these critiques of utilizing government data to measure the impact of disability on worklife expectancy should be considered.
For the past three decades, economists have devoted effort to ranking economics journals based upon their influence to the profession and the broader social science literature. It is generally safe to say that economists engaged in forensic matters represent a very small percentage of economists throughout the United States and the world. Nonetheless, it is important to note that two researchers from France produced a working paper ranking 1,168 economics journals throughout the world (Combes, Pierre-Philippe and Laurent Linnemer. 2010. “Inferring Missing Citations: A Quantitative Multi-Criteria Ranking of all Journals in Economics.”).
In performing the rankings they include “AAA”, “AA”, “A”, “B”, “C”, and “D” classifications of journals. Typically, in the United States, all “A” and “B” journals are worthy of consideration at institutions with a “publish or perish” standard. While some institutions, particularly those with a strong teaching orientation, may include some “C” journals, it is highly improbable that any institution would consider a “D” journal to guide tenure or promotion decisions.
These rankings are important to the judicial system at the district court level because the only criticisms leveled at utilizing government data to measure worklife expectancy for individuals with a disability have been published in the Journal of Forensic Economics and the Journal of Legal Economics. Each of these journals has a “D” ranking.
The supposed controversy existing over the issue of a disability-based worklife expectancy is a tempest in a tea pot. The severe criticism surrounding the issue of disability-based worklife expectancy has been published in journals that are less than reputable. In part, as a result of these publications, hundreds of challenges have been brought specific to disallowing testimony regarding reduction of worklife expectancy for persons with disability and surprisingly, a few have been successful.
Approximately 27 years ago, the first worklife expectancy values for persons with a disability were published (Gamboa, Anthony M. Jr. 1987. Worklife Expectancy of Disabled versus Non-disabled Persons by Sex and Level of Educational Attainment. Louisville, KY: Vocational Economics Press.). Twelve years later, in 1999, the first article critical of disability-based worklife expectancy was published in the Journal of Forensic Economics (Skoog & Toppino 1999). Over time, appeals brought forward specific to the issue of disability-based earnings and worklife expectancy were considered at the Appellate Court level.
There are eight appellate decisions supporting the lower courts in allowing testimony specific to the methodology employed in assessing earning capacity loss as well as the effect of disability on earnings and worklife expectancy (Anderson, Kenneth v. Tommie L. Rogers, et al. 2012. No. CW 12-00542 (State of Louisiana Court of Appeal, May 29); Knitowski, Dennis J. v. Frank M. Gundy, Jr. and State of New Jersey and John Glover. 2011. A-5945-09T1 (Superior Court of New Jersey, Appellate Division, November 10); Johnson v. CSX Transportation, Inc. 2006/2008. 04 L 4146 (Appellate Court of Illinois, December 24); Cox and Tube City LLC, d/b/a/ Olympic Mill Services v. Allen Matthews. 2007. 45A05-0803-CV-183 (Court of Appeals of Indiana, February 12); Stichnoth, Justin v. Shafer & Freeman Lakes Enviornmental Conservation Corporation. 2007. 91A04-0611-CV-661 (Court of Appeals of Indiana, November 29); Shaheen v. Advantage Moving and Storage, Inc. and William T. Urban. 2003/2006. 1-04-1079 (Appellate Court of Illinois, December 1); Nilavar v. Osborn. 2000. C.A. No. 99-CA-53, T.C. No. 96-CV-0343 (Court of Appeals of Ohio, April 7); Figurski v. Trinity Health-Michigan, 2015. No. 310896, L.C. No. 11-026466-NH (Michigan Court of Appeals., March 5).)
There is a wealth of information and responses to challenges specific to methodology and worklife expectancy as it pertains to persons with disability. Both the appellate decisions and scores of responses to both Daubert and Frye challenges are available by contacting the authors.
It is essential for attorneys who represent clients with a partial disability to hire experts that utilize government data that permits calculation of a worklife expectancy value. When a client has an established permanent impairment with functional limitations associated with performing work, it is probable that the case will be significantly undervalued if the future worklife expectancy reduction is not considered. It is common that injuries of both physical and cognitive nature worsen with the passage of time. There is a keen awareness of the negative effect aging has on traumatic-brain injury (TBI) in part because of recent research, but also as a function of the recent focus on football-related head injury within the National Football League.
Similarly, many orthopedic injuries worsen with the passage of time; particularly those injuries resulting in a fusion that often results in adjacent facet syndrome causing additional fusions over time. Physicians with a specialty in Physical Medicine and Rehabilitation (Physiatrists) work with patients after maximum medical improvement is achieved. These physicians can attest to the effect aging has on both cognitive and physical impairment as the aging process unfolds. They opine from a clinical perspective on precisely what data from the ACS tells us about employment levels. Beginning in the late forties or early fifties, employment levels begin to decline as a function of aging. With the interaction effect of aging and physical or cognitive impairment, the decline is more precipitous.
Permanent injury results often in both past wage loss and more importantly future loss of earning capacity. When estimating into the future, rational decision making requires the use of probabilistic decision making in terms of what is most likely to occur for a specific individual with a specific type of impairment. Through the use of government-collected data, a qualified expert can define as an aide of the trier-of-fact the probable level of worklife expectancy reduction that will occur through decreases in employment.
Dr. Joseph T. Crouse is a Labor Economist with Vocational Economics, Inc. and works out of the Los Angeles, CA office.
Chris Reyes is a Vocational Analyst with Vocational Economics, Inc. and works out of the Los Angeles, CA office.
Dr. A. M. Gamboa, Jr., is a Senior Analyst with Vocational Economics, Inc. He is based in Palm Beach Gardens, FL.
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